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import typed_ast.ast3 as ast
import util.error as err
import typesys.mytypes as mytypes
from libbase.libfuncs import *
def get_func_info(func_name, module_names):
if module_names:
main = module_names[0]
sub = module_names[1:] if len(module_names) > 1 else []
info = module_to_info(main, sub... |
from itertools import combinations
import numpy as np
from torch.autograd import Variable
import torch as th
import torch.nn as nn
import torch.nn.functional as F
from components.transforms import _check_inputs_validity, _to_batch, _from_batch, _adim, _bsdim, _tdim, _vdim, _check_nan
from models.basic import RNN as Re... |
import datetime
from django.db import models
from django.contrib.auth.models import User
from django.conf import settings
from tagging.fields import TagField
from markdown import markdown
class Category(models.Model):
title = models.CharField(max_length=250,
help_text='Maximum 250 characters.')
description... |
from keras.callbacks import ReduceLROnPlateau#, LearningRateScheduler
from keras.layers import (Input, Conv2D, BatchNormalization, ZeroPadding2D, Dropout,
GlobalAveragePooling2D, Activation, Dense, add)
from keras.models import Model
from keras import optimizers
from keras import regularizers
... |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import torch
from torch.jit import script, trace
import torch.nn as nn
from torch import optim
import torch.nn.functional as F
import csv
import random
import re
import o... |
import requests
import os
import pandas as pd
from flask import Flask, render_template, request, redirect
#from bokeh.plotting import figure
#from bokeh.embed import components
from spotipy.oauth2 import SpotifyClientCredentials
import spotipy
import dill
import spotipy.util as util
import spotipy.oauth2 as oauth2
imp... |
import abc
import matplotlib.patches as patches
import numpy as np
class IllustratorElement(abc.ABC):
"""base class for optical illustrator
elements"""
mode_plot_kwargs = {'color':'k',
'solid_capstyle':'round'}
width = 1
@abc.abstractmethod
def draw(self, ax):
... |
# -*- coding: utf-8 -*-
"""
A module for decoding "Actions" additional PSD data format.
"""
from __future__ import absolute_import, unicode_literals
import collections
from psd_tools.utils import read_unicode_string, read_fmt
from psd_tools.constants import OSType, ReferenceOSType, UnitFloatType
Descriptor = collect... |
import ast
import re
import numpy as np
import pandas as pd
def isnull(x):
"""
Return boolean indicating whether a value is null.
"""
if pd.isnull(x):
return True
elif str(x).lower() in ['nan', 'none', 'null', 'n/a']:
return True
else:
return False
def map_on_off(x):
... |
from functools import wraps, partial, reduce
import numpy as np
import torch
import torch.optim
from torch.autograd import grad
import utils.distributions as my_dists
from .probabilistc_model import ProbabilisticModel
def normalize_per_dimension(prob_model, dims, func, name):
if dims == 'all':
dims = r... |
from django.db.models import query
from django.db.models.fields import Field
from django.db.models.query import QuerySet
from django.shortcuts import render, redirect
from django.forms import inlineformset_factory
from django.contrib import messages
from django.contrib.auth import authenticate, login, logout
from djan... |
# -*- coding: utf-8 -*-
"""
Created on Fri Dec 28 21:40:15 2018
@author: dylan
"""
import numpy as np
import matplotlib.pyplot as plt
import math as m
from mpl_toolkits.mplot3d import axes3d
MAGCONFIGR=[
[1, 0, 0],
[2, 0, 0],
[-1, 0, 0],
[-2, 0, 0],
[0, 1, 0],
[0, 2, 0],
[0,-1, 0],
[... |
from tqdm import tqdm
import matplotlib.pyplot as plt
from functools import partial
import numpy as np
import tensorflow_probability as tfp
from tensorflow_probability.python.internal import nest_util
from tensorflow_probability import bijectors as tfb
import tensorflow as tf
from tensorflow_probability.python.vi impo... |
from .mixins import *
from .types import *
from .decorators import *
import json
def build_param_message(missing_params):
return "The following parameters were missing: {0}".format(", ".join(missing_params))
def build_param_type_message(invalid_params):
return "The following parameters were of the wrong type: {0}".... |
import json
import os
from unittest import TestCase, skip, expectedFailure
import Gui.jumpcutterGui as J_gui
# constants
PROJECT_ROOT = os.path.normpath(os.path.join(__file__, '..', '..'))
DOWNLOAD_FOLDER = r"C:\Users\frank\Downloads"
GUI_FOLDER = os.path.join(PROJECT_ROOT, "Gui")
SETTINGS_FILE = os.path.join(GUI_F... |
# Copyright (c) 2015. Mount Sinai School of Medicine
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law o... |
#!/usr/bin/env python3
import os
import subprocess
import sys
from Bio import SeqIO
from Bio.Seq import Seq
from Bio.SeqRecord import SeqRecord
from simplesam import Reader
#==========================================================================================================
# COMMANDS LIST
TRINITY = 'Trinity ... |
# -*- coding: utf-8 -*-
from __future__ import absolute_import
import json
import logging
import sys
from time import sleep
from Crypto.Hash import SHA256
from cached_property import cached_property
from standardjson import StandardJSONEncoder
import requests
from six import string_types
if not logging.getLogger().... |
"""
copyright <NAME>
11/08/2021
"""
class Solution:
def findMedianSortedArrays(self, nums1: list[int], nums2: list[int]) -> float:
"""
:rtype: object
"""
i = 0
j = 0
return_list = []
while i <= (len(nums1) - 1) and j <= (len(nums2) - 1):
if num... |
import math
import torch
from torch.optim.lr_scheduler import _LRScheduler, LambdaLR
#def get_cosine_with_hard_restarts_schedule_with_warmup(
# optimizer: Optimizer, num_warmup_steps: int, num_training_steps: int, num_cycles: int = 1, last_epoch: int = -1
#):
# """
# Create a schedule with a learning rate tha... |
from abc import ABCMeta, abstractmethod
from typing import Optional
import msal
from .. import session
from ..auth import microsoft, security, yggdrasil
class AuthenticatedUser(metaclass=ABCMeta):
def __init__(self, access_token: str, refresh_token: str) -> None:
self.__name = None
self.__uuid =... |
import os
import pandas as pd
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.utils.data import DataLoader, TensorDataset
from utilities import printf, ModelCoordinator, main
from pums_downloader import download_pums_data, get_pums_data_path, datasets
from opendp.network.odometer import... |
# author: <NAME>
# functionality: extraction, training and validation
import dynamic_analysis
import utility
from time import time
import pickle
import numpy as np
import random
classes = [
'Benign',
'Malware/Backdoor',
'Malware/Trojan',
'Malware/Trojandownloader',
'Malware/Tro... |
# -*- coding: utf-8 -*-
#
# Copyright 2020 AllanKT.
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or ag... |
from django.http import HttpResponse
from django.shortcuts import render
from store.models import *
from django.core.mail import EmailMessage
from django.views.decorators.gzip import gzip_page
from django.http import StreamingHttpResponse
import cv2
import threading
import numpy as np
@gzip_page
def Home(request):
... |
# -*- coding: utf-8 -*-
import os
import sys
import warnings
from time import time
from docopt import docopt
import colorful
import tagexpressions
from . import __VERSION__
from .core import Core
from .core import Configuration
from .loader import load_modules
from .matcher import merge_steps
from .stepregistry impo... |
"""Store game events in database
Usage:
munerator [options] store
Options:
-v --verbose Verbose logging
--context-socket url ZMQ socket for conext event [default: tcp://127.0.0.1:9002]
--database ip:port Host and port for mongo database [default: 127.0.0.1:27017]
--rcon-socket url Z... |
#!/usr/bin/env python3
import argparse
import sys
import os
import re
import numpy
from Bio import Entrez
from Bio import SeqIO
from vars import COV_DIR, EMAIL
# NCBI Taxonomy ids:
# 333387: single record for testing
# 2697049: Severe acute respiratory syndrome coronavirus 2
# 694009 (parent of 2697049): Severe acute... |
'''
Created on Aug 20, 2010
@author: joel
'''
import numpy
def applyweights(wp, vp):
from numpy import newaxis
wp = wp.reshape(wp.shape + (1,)*(3-len(wp.shape)))
if len(vp.shape) == 2: vp = vp[:,:,newaxis]
wvp = numpy.sum(wp[:,newaxis] * vp[:,:,newaxis,:], axis=3)
# print "applyweights %s, %s, ... |
#----------------------------------------------------------------------------------------------------------
# <NAME>
# <EMAIL>
# May 2016
# v1.1
#----------------------------------------------------------------------------------------------------------
import nuke
import operator
def AlignNodes(direction):
#---... |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright 2018 GoPro Inc.
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
#... |
import os
import sys
import platform
from ._constants import msg_file_not_found
import re
# IN: persistent_peers = "xxxx@yyy:dddd"
# OUT:persistent_peers = ""
# or
# IN: persistent_peers = ""
# OUT:persistent_peers = "xxxx@yyy:dddd"
def replaceKey(keystring,filename,quotechar='"',value=""):
fullpath = os.path.re... |
"""
generic_dynamics.py
Implements the `GenericDynamics` object by subclassing the `BaseDynamics`
class.
Author: <NAME>
Date: 7/15/2020
"""
from __future__ import absolute_import, division, print_function
import time
import tensorflow as tf
try:
import horovod.tensorflow as hvd
HAS_HOROVOD = True
except Impo... |
# positivity_test.py
# Original by 솜시좋은장씨
# Editted by <NAME> (전한나), <NAME> (황병호)
# positivity_test.py는 긍정/부정 정도 판별 모델을 직접 이용하는 모듈을 모아놓은 파일이다.
# Licensed by
# https://somjang.tistory.com/entry/Keras%EA%B8%B0%EC%82%AC-%EC%A0%9C%EB%AA%A9%EC%9D%84-%EA%B0%80%EC%A7%80%EA%B3%A0-%EA%B8%8D%EC%A0%95-%EB%B6%80%EC%A0%9... |
from collections import OrderedDict
from rest_framework import status
from drf_yasg.inspectors.base import FieldInspector, NotHandled
from drf_yasg import openapi, utils, generators
from drf_yasg.inspectors import (
SwaggerAutoSchema, swagger_settings, field as field_insp, CoreAPICompatInspector
)
from . import fie... |
# Copyright 2020 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, ... |
import argparse
from grid import *
from utility.logconfig import *
import logging
script_dir = os.path.dirname(os.path.realpath(__file__))
class Element(GridItemType):
def __init__(self, name, image, factor):
GridItemType.__init__(self, name, image)
self.factor = factor
class Board(Grid):
# ... |
import numpy as np
#simple implementation of a doubly linked list
#a doubly linked list has a head and a tail element
#elements can be appended and removed from either end of the list
class LinkedList:
def __init__(self):
self.size = 0
self.head = None
self.tail = None
def add_hea... |
import numpy as np
from sklearn.decomposition import PCA, IncrementalPCA, TruncatedSVD
from scipy.sparse import issparse
from scipy.sparse.linalg import LinearOperator, svds
from sklearn.utils import check_array , check_random_state
from sklearn.utils.extmath import svd_flip
import warnings
"""
The following code is i... |
from django.shortcuts import render, redirect
from django.conf import settings
from rest_framework import viewsets, mixins, status
from rest_framework.permissions import AllowAny, IsAuthenticated
from rest_framework.response import Response
from rest_framework.decorators import permission_classes, action, api_view
impo... |
import numpy as np
import tqdm
import gym
class ToyEnv(gym.Env):
def __init__(self, problem='4state'):
self.action_space = gym.spaces.Discrete(2)
self._state = None
self._diamond = None
self._diamond_2 = None
self.fn = {'4state': self._4_state_problem, '5state': self._... |
from collections import OrderedDict
from typing import Dict
import torch
from .global_var import config
from .block_layer import CheckpointBlock
from . import nccl
import io, pickle
def _save_to_state_dict(model : torch.nn.Module, destination, prefix):
if isinstance(model, CheckpointBlock):
if config['rank... |
import time
import datetime
from typing import Any, Dict
import sqlalchemy
from sqlalchemy.sql.expression import text
from utils import deserialize
from .config import Config
class UserNotFoundError(Exception):
pass
class BindError(Exception):
def __init__(self, err_msg: str) -> None:
super().__in... |
# ex:ts=4:sw=4:sts=4:et
# -*- tab-width: 4; c-basic-offset: 4; indent-tabs-mode: nil -*-
"""
BitBake 'Event' implementation
Classes and functions for manipulating 'events' in the
BitBake build tools.
"""
# Copyright (C) 2003, 2004 <NAME>
#
# This program is free software; you can redistribute it and/or modify
# it u... |
import math
import os
# Solution
def part1(data, print_coords=False):
grid = create_grid(data)
result_sum = 0
for xc in range(len(grid)):
for yc in range(len(grid[xc])):
if grid[xc][yc] == 0:
continue
sight = dict()
for xt in range(len(grid)):
... |
"""
:Created: 31 October 2014
:Author: <NAME>
"""
import abc
import inspect
import logging
import random
from .exceptions import InvalidConditionError, UndefinedConditionError
__all__ = ["Condition", "CompareCondition"]
logger = logging.getLogger("condition")
class Condition:
"""
A condition which evalu... |
# Copyright (C) 2016 Hewlett Packard Enterprise Development LP
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... |
'''tf.Graph processor used for training'''
from .shell_filter import ShellFilter
from .shell_reorder import ShellReorder
from .scaler import DataScaler, NormDataScaler
from .patcher import Patcher
from .reshaper import Reshaper, Joiner
from .base import CombineDatasets
from .io import load_tfrecord_data
class Traini... |
from scipy.stats import norm
from scipy.linalg import cholesky
from .. import main
import numpy as np
#####
'''
The correlation coefficient for the Nataf transformation is evaluated, following:
<NAME>. "Evaluating correlation coefficient for Nataf transformation." Probabilistic Engineering Mechanics 37 (2014): 1-... |
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 16 13:31:34 2021
@author: <NAME>
"""
import seaborn as sns
import streamlit as st
import pandas as pd
from datetime import timedelta
import numpy as np
import matplotlib
import matplotlib.pyplot as plt
import datetime
def text_area(label):
final_comment.append(label... |
import sys
from inspect import signature
from types import FunctionType
from typing import (
TYPE_CHECKING,
Any,
Callable,
Dict,
List,
Optional,
Tuple,
Union,
)
from warnings import warn
from magicgui import magicgui
from napari_plugin_engine import HookImplementation, PluginManager
fr... |
# Author: <NAME> (<EMAIL>)
from typing import List, Type, Union
import numpy as np
from actor.shape_actor import ShapeActor
from observer.event.events import CustomEvent
from observer.base_observer import BaseObserver
from shape.point_2d import Point2D
from shape.polygon_2d import Polygon2D
from shape.polyline_2d i... |
from django.core.urlresolvers import reverse
from django.shortcuts import render_to_response, get_object_or_404
from django.http import HttpResponseRedirect, Http404
from django.template import RequestContext
from django.contrib.auth.decorators import login_required
from django.contrib.syndication.views import feed
f... |
import enum
from torch.utils.data import Dataset
from torch.utils.data._utils.collate import default_collate
from typing import Dict, List, Tuple, Union
import json
from transformers import PreTrainedTokenizer
import numpy as np
import collections
from tqdm import tqdm
import re
import copy
FCInst = collections.name... |
#!/usr/bin/env python
import unittest
import pexpect
from robot.version import get_version
TIMEOUT_SECONDS = 2
child = None
def check_result(pattern):
index = child.expect([pattern, pexpect.EOF, pexpect.TIMEOUT],
timeout=TIMEOUT_SECONDS)
try:
assert index == 0
except A... |
from exceptions import DeviceTimeoutError
from mqtt import MqttMessage, MqttConfigMessage
from interruptingcow import timeout
from workers.base import BaseWorker
import logger
import json
import time
from contextlib import contextmanager
import bluepy.btle as btle
import argparse
import signal
import struct
import sy... |
#!/usr/bin/env python
'''
Custom advanced radar controller
================================
'''
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.animation as animation
import sorts
from sorts.radar.scans import Fence
import sorts
eiscat3d = sorts.radars.ei... |
from __future__ import annotations
import argparse
import atexit
import itertools
import pathlib
import shlex
import shutil
import signal
import subprocess
import sys
import traceback
from typing import Dict, List, Optional, Tuple
from pyoomph import ast, ast2ir, ast_transformer, c_output, ir, parser
python_code_dir... |
# Copyright (c) 2017-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the license found in the LICENSE file in
# the root directory of this source tree. An additional grant of patent rights
# can be found in the PATENTS file in the same directory.
import itertools
import numpy as n... |
import os.path
import torchvision.transforms as transforms
import numpy as np
import json
import nibabel as nib
from data.base_dataset import BaseDataset
from configurations import *
from util.image_property import hash_file, normalize_image, slice_with_neighborhood
def get_domain_code(path):
code = np.zeros(5)
... |
from hydroDL.data import Dataframe, DataModel
from hydroDL import utils
from .io import *
from .subset import *
from . import SMAP
class DataframeCsv(Dataframe):
def __init__(self, rootDB, *, subset, tRange):
super(DataframeCsv, self).__init__()
self.rootDB = rootDB
self.subset = subset
... |
"""Task 3 in project"""
import matplotlib.pyplot as plt
import numpy as np
from numba import njit, prange
from tqdm import tqdm
A = "TGGAATTCTCGGGTGCCAAGGAACTCCAGTCACACAGTGATCTCGTATGCCGTCTTCTGCTTG"
def read_file(filename: str = "..\\data\\s_3_sequence_1M.txt"):
with open(filename, "r") as f:
return f.r... |
import uuid
import datetime
from django.conf import settings
from django.db import models
from django.utils import timezone
from cwfollowup.utils.jobs.request_file_download_id import request_file_download_id
from cwfollowup.utils.jobs.request_file_list import request_file_list
from cwfollowup.utils.jobs.request_job_s... |
from typing import Optional, Callable, Any, List, Tuple
import mdtraj as md
import numpy as np
from dataclasses import dataclass
from .. import log
_log = log.getLogger(__name__)
@dataclass
class CV(object):
"""
Collective variable class with an id and a generator to convert every frame in a trajectory to ... |
from pyspark_proxy.proxy import Proxy
__all__ = [
'DataType', 'IntegerType', 'LongType', 'StringType', 'FloatType',
'DoubleType', 'DecimalType', 'LongType', 'StructType', 'NullType',
'NumericType', 'BinaryType', 'FractionalType', 'DateType', 'TimestampType',
'ByteType', 'ShortType', 'ArrayType', 'Struc... |
"""
Predict labels with a model.
"""
import logging
import zipfile
from os import makedirs, walk
from os.path import exists, join, basename
from shutil import rmtree
import jams
import numpy as np
from sklearn.externals.joblib import dump, load
from tensorflow.python.keras import backend as K
def predict_from_models... |
import pidsim.ml_simulator as ml_kinetics
import pnptransport.finitesource as pnpfs
import logging
import os
import numpy as np
from datetime import datetime
from pidsim.parameter_span import create_filetag
import traceback
import random
def get_logger(output_path, file_tag, **kwargs):
name = kwargs.get('name', '... |
""" Utilities for isgm
Best to keep these separate from the Class modules
"""
from __future__ import print_function, absolute_import, division, unicode_literals
# Python 2 & 3 compatibility
try:
basestring
except NameError:
basestring = str
import pdb
import numpy as np
import warnings
import json
from astr... |
import argparse
import sys
import os
import json
import datetime
import sys as _sys
from gettext import gettext as _, ngettext
from msgraph import helpers
from common.BaseCommand import BaseCommand
from common.ResultAndData import *
from common.Instance import Instance
from common.CaughtParserError i... |
import os
import sys
import io
from datetime import datetime
import argparse
import numpy as np
from PIL import Image
import tensorflow as tf
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d, Axes3D
from PIL import Image
import models.argo_nu as models
parser = argparse.ArgumentParser()
parser.a... |
#!/usr/bin/env python
import os
import urllib
import json
import dateutil.parser
from google.appengine.api import users
from google.appengine.ext import ndb
from datetime import timedelta, date
import jinja2
import webapp2
JINJA_ENVIRONMENT = jinja2.Environment(
loader=jinja2.FileSystemLoader(os.path.dirname(_... |
# Copyright 2019 Katteli Inc.
# TestFlows.com Open-Source Software Testing Framework (http://testflows.com)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/lice... |
from datetime import date, datetime, timezone
from enum import Enum
from unittest.mock import Mock
import pytest
from dateutil import tz
from todoms.converters.basic import (
AttributeConverter,
ContentAttrConverter,
DateAttrConverter,
DatetimeAttrConverter,
EnumAttrConverter,
IsoTimeAttrConve... |
import inspect
import json
import os
import pandas as pd
import requests
from powersimdata.utility.distance import find_closest_neighbor
from tqdm import tqdm
import prereise
def aggregate_ba_demand(demand, mapping):
"""Aggregate demand in BAs to regions as defined in the mapping dictionary
:param pandas.D... |
import os
import sys
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from sklearn.externals import joblib
from collections import OrderedDict
import re
from os.path import dirname, join, abspath
from sklearn.model_selection import cross_val_score
def plot_coefficients(model, top_features=20):
... |
import shutil
import os
# Get the current path of the script
script_dir = os.path.dirname(os.path.abspath(__file__))
# Get the root folder of the ETL
etl_dir = os.path.abspath(os.path.join(script_dir, os.pardir))
# Get the ETL repository folder
include_dir = os.path.join(etl_dir, 'include')
# Get the ETL heade... |
from Sorts import count_sort
def rabin_karp_matching(
text: str,
pattern: str,
max_char: int = 256,
prime: int = 999983) -> bool:
'''
Pattern matching in a string using rabin karp algorithm.
Takes a text and pattern as input and returns true
if the pattern oc... |
import numpy as np # NOT IN BOOK
from matplotlib import pyplot as plt # NOT IN BOOK
def load():
import numpy as np
from scipy import sparse
data = np.loadtxt('data/ml-100k/u.data')
ij = data[:, :2]
ij -= 1 # original data is in 1-based system
values = data[:, 2]
reviews = sparse.csc_matri... |
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
from nose.tools import assert_equal, assert_raises
from numpy.testing import assert_array_almost_equal, assert_array_equal
import numpy as np
from .... import load_image
from ....testing import funcfile
... |
#Python MemeCreationBot: creates a meme based on user input and imgflip.com internet connection
import discord
import random
from discord.ext import commands
import time
from selenium import webdriver
from webdriver_manager.chrome import ChromeDriverManager
#list of lists for each meme; each list's elements ar... |
# -*- coding: utf-8 -*-
"""
Created on Tue Dec 12 10:10:41 2017
@author: ibari
"""
import os
import warnings
from distutils.spawn import find_executable
__LOCAL__ = ['sensor', 'projection', 'orbit', 'polarizations', 'acquisition_mode',
'start', 'stop', 'product', 'spacing', 'samples', 'lines']
class St... |
import inspect
import subprocess
from collections import defaultdict
from functools import wraps
import pytest
# deploy statuses
STATUS_BEFORE, STATUS_AFTER, STATUS_CRUSHED = "before", "after", "crushed"
class State:
""" class for common vars """
terminal = None # terminal for printing
deploy_cmd = Non... |
#***************************************************************************
# _ _ ____ _
# Project ___| | | | _ \| |
# / __| | | | |_) | |
# | (__| |_| | _ <| |___
# \___|\___/|... |
from SALib.sample import saltelli
from SALib.analyze import sobol
from SALib.test_functions import Ishigami
import numpy as np
from numpy import cos,sin,tan,pi
from scipy.integrate import odeint
from numpy.linalg import norm
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib
#matplotlib.rcParams['tex... |
# Acumos - Apache 2.0
import hashlib
import fakeredis
from acumos_proto_viewer.run_handlers import MODEL_SELECTION, MESSAGE_SELECTION
from acumos_proto_viewer.run_handlers import get_source_index, handle_data_post, handle_onap_mr_put, handle_onap_mr_delete, get_model_properties, get_modelid_messagename_type
from acum... |
import os
import tempfile
import zipfile
from datetime import timedelta
from io import BytesIO
from PIL import Image, ImageFont, ImageDraw
from pycaption.base import BaseWriter, CaptionSet, Caption
HEADER = """st_format 2
SubTitle\tFace_Painting
Tape_Type\t{tape_type}
Display_Start\tnon_forced
Pixel_Area\t(2 479)
Di... |
"""Group.py: NeoPixel Indicator Module."""
import threading
import time
from typing import Any, List, overload
import neopixel
from npin.Constants import Color
from npin.Counter import SharedCounter
from npin.Element import Element
class Group:
"""Make this a docstring."""
def __init__(
self, elem... |
import csv
import util
import numpy as np
import statistics
import argparse
from os.path import join
from collections import OrderedDict
from tabulate import tabulate
CLI = argparse.ArgumentParser()
CLI.add_argument("fold", help="Absolute path of the fold json file")
CLI.add_argument("k", help="Maximum number of rec... |
import subprocess
import time
import threading
import os
import json
import web
####################################################
# run background services to receive web hooks
####################################################
# agent webhook callbacks
class webhooks:
def GET(self, topic):
# just fo... |
import math
import numpy as np
from bwmorph_thin import bwmorph_thin as bwmorph
def my_xor_infile(u_infile, u0_GT_infile):
temp_fp_infile = np.zeros(u_infile.shape, np.uint8)
temp_fp_infile[(u_infile == 0) & (u0_GT_infile == 1)] = 1
temp_fn_infile = np.zeros(u_infile.shape, np.uint8)
temp_fn_infile[... |
from typing import List
from tensorflow.keras import Model, Input
from tensorflow.keras import layers
from datetime import datetime
from pathlib import Path
import tensorflow as tf
from tensorflow.keras import losses, metrics
from tensorflow.keras.callbacks import TensorBoard
class ResidualBlock(layers.Layer):
... |
"""Tools for creating graphical visualizations of auction algorithms."""
import re
import json
try:
from IPython import display
except ImportError:
pass
class AuctionGraphVisualizer(object):
"""Abstract base class for graph visualizations."""
def draw_graph(self, graph):
raise NotImplementedE... |
import os
import cv2
import sys
import torch
import pprint
import torch.nn as nn
import torch.nn.functional as F
import arcsim
import gc
import time
import json
import gc
import numpy as np
from datetime import datetime
import pytorch3d
from pytorch3d.structures import Meshes
from pytorch3d.io import load_obj
from py... |
#!/home/wli/env python3
# -*- coding: utf-8 -*-
"""
Title: color normalization
==========================
Created: 10-31-2019
Python-Version: 3.5
Description:
------------
This module is used to do the color normalization for image patches.
Input:
template image for color normalization
template_image_path = '/ra... |
"""
plot_vertical_cross_section_from_netcdf.py: plot the vertical cross section from the netcdf file.
"""
import click
import matplotlib.pyplot as plt
import numpy as np
from scipy.interpolate import RegularGridInterpolator
from netCDF4 import Dataset
def generate_vcs_mesh(lon1, lat1, lon2, lat2, dep1, dep2, rh, rdep... |
import sys
import inspect
import weakref
from contextlib import contextmanager
from collections import OrderedDict
import numpy as np
from scipy.spatial import cKDTree
_SHAPE_ASSERTIONS = True
def assert_shape(arr, shape, label='array'):
'''
Raises a ValueError if `arr` does not have the specified shape
... |
"""Defines several services for Google OAuth implementation."""
import os
import logging
import json
import requests
from oauthlib.oauth2 import WebApplicationClient
from urllib import request as urllib_request
from flask import request, redirect
from flask_login import login_user
from . import auth_mapper
logger = l... |
# -*- coding: utf-8 -*-
"""
Created on Mon Nov 5 13:04:16 2018
Copyright (c) <NAME>
Author email: <<EMAIL>>
Description:
This program was originally created to calculate the evaluation
statistics of deblurred images. However, this program can be used
to evaluate any image with another image.
... |
# Copyright 2022 @ReneFreingruber
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in... |
import os
import glob
import h5py
import numpy as np
from mask_DC2 import read_selections
from mask_DC2 import mask_cat
lowz_lib = '/gpfs/mira-fs0/projects/DarkUniverse_esp/dkorytov/data/Galacticus/low_z/galaxy_library/*.hdf5'
hiz_lib = '/gpfs/mira-fs0/projects/DarkUniverse_esp/dkorytov/data/Galacticus/high_z/galaxy_l... |
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